Bioinformatics Core

The Bioinformatics Core, led by Dr. Reinhard Schneider, is responsible for the efficient data flow between the experimental groups and the theoretical and medical oriented groups at the Luxembourg Centre for Systems Biomedicine. Furthermore the group develops new algorithms in various fields to help to understand and interpret the data.

About the Bioinformatics Core group

The core facility group is so to say inside the tornado. We get a huge amount of data from the experimental groups, which we have to handle, store and categorize. In the past decades nearly all technologies in the Life Sciences were tailored for high throughput data production. As a result we have to deal with PetaBytes of data (1 PetaByte corresponds to more than 13 years of High-definition TV or 500 billion pages of standard printed text). We have to setup and run large computer and storage facilities with thousands of processors and an ever-increasing number of hard disks. A significant part of the budget of a modern Life Science Institute today is spend for information technology.

After we manage to physically handle the huge amount of data we face the next challenge to deploy and develop techniques to run a cost and time efficient data analysis pipeline. Due to the amount of data we need to implement automatic workflows, which apply a range of prediction and filtering steps such that we can focus on the “interesting” data and don’t waste time with the rest. Here we need to bring the different expertise’s of our team together. This typically requires the close collaboration of computer scientist and biologist covering a broad spectrum of different disciplines.

Furthermore we try to close the gap and shortcomings of existing methods and algorithms by refining and developing our own implementations and extensions. In a few areas we do basic research on our own. One such topic at the LCSB is for example the visualization bottleneck, which we currently face. Here we develop completely new tools and techniques to allow a better interpretation of the data, to provide new insights and to generate new hypothesis regarding the functioning of complex biological systems.

Given the challenges described above our team has a very diverse academic background - from computer science, biology and biochemistry, mathematics and physics, all the way to medicine. All of us have a good sense for computer science and the manipulation of large volumes of data. In addition, members of our team need to have the ability to conscientiously listen to researchers in other fields - the only way to bridge biology, computer and medical science.